Determining aboveground biomass of the forest successional chronosequence in a test-site of Brazilian Amazon through X- and L-band data analysis

João Roberto Santos; Camila Valéria de Jesus Silva; Lênio Soares Galvão; Robert Treuhaft; José Claudio Mura; Soren Madsen; Fábio Guimarães Gonçalves; Michael Maier Keller

doi:10.1117/12.2066031

12 August 2014 Determining aboveground biomass of the forest successional chronosequence in a test-site of Brazilian Amazon through X- and L-band data analysis

João Roberto Santos, Camila Valéria de Jesus Silva, Lênio Soares Galvão, Robert Treuhaft, José Claudio Mura, Soren Madsen, Fábio Guimarães Gonçalves, Michael Maier Keller

Author Affiliations +

Proceedings Volume 9229, Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014); 92291E (2014) https://doi.org/10.1117/12.2066031
Event: Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 2014, Paphos, Cyprus

Abstract

Secondary succession is an important process in the Amazonian region with implications for the global carbon cycle and for the sustainable regional agricultural and pasture activities. In order to better discriminate the secondary succession and to characterize and estimate the aboveground biomass (AGB), backscatter and interferometric SAR data generally have been analyzed through empirical-based statistical modeling. The objective of this study is to verify the capability of the full polarimetric PALSAR/ALOS (L-band) attributes, when combined with the interferometric (InSAR) coherence from the TanDEM-X (X-band), to improve the AGB estimates of the succession chronosequence located in the Brazilian Tapajós region. In order to perform this study, we carried out multivariate regression using radar attributes and biophysical parameters acquired during a field inventory. A previous floristic-structural analysis was performed to establish the chronosequence in three stages: initial vegetation regrowth, intermediate, and advanced regrowth. The relationship between PALSAR data and AGB was significant (p<0.001) and results suggested that the “volumetric scattering” (Pv) and “anisotropy” (A) attributes were important to explain the biomass content of the successional chronosequence (R²_adjusted= 0.67; RMSE = 32.29 Mg.ha^-1). By adding the TanDEM-derived interferometric coherence (Υi) into the regression modeling, better results were obtained (R²_adjusted = 0.75; RMSE = 28.78Mg.ha-¹). When we used both the L- and X-band attributes, the stock density prediction improved to 10.8 % for the secondary succession stands.

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João Roberto Santos, Camila Valéria de Jesus Silva, Lênio Soares Galvão, Robert Treuhaft, José Claudio Mura, Soren Madsen, Fábio Guimarães Gonçalves, and Michael Maier Keller "Determining aboveground biomass of the forest successional chronosequence in a test-site of Brazilian Amazon through X- and L-band data analysis", Proc. SPIE 9229, Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 92291E (12 August 2014); https://doi.org/10.1117/12.2066031

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